Finding Meaningful Detections: False Discovery Rate Control in Correlated Detection Maps - Archive ouverte HAL
Communication Dans Un Congrès Année : 2021

Finding Meaningful Detections: False Discovery Rate Control in Correlated Detection Maps

Résumé

The detection of faint sources is a key step in several areas of signal and image processing. The reliability of the detection depends on two key components: (i) the detection criterion used to derive detection maps in which the signature of a source takes the form of a detection peak, and (ii) the extraction procedure identifying the meaningful detections. In this work, the expected false discovery rate guides the selection of meaningful detections. A procedure is designed to account for correlations in the detection maps. This prevents the issue of the multiple detections of a single source and corrects the number of effective independent tests performed. The proposed approach is evaluated on an astrophysical application: the detection of exoplanets by high-contrast imaging.
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Dates et versions

hal-04695057 , version 1 (11-09-2024)

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Citer

Olivier Flasseur, Loic Denis, Eric Thiebaut, Maud Langlois. Finding Meaningful Detections: False Discovery Rate Control in Correlated Detection Maps. 2020 28th European Signal Processing Conference (EUSIPCO), Jan 2021, Amsterdam, France. pp.1896-1900, ⟨10.23919/Eusipco47968.2020.9287847⟩. ⟨hal-04695057⟩
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